Mapping of Groundwater Quality in Northern Sinai Using GIS ...€¦ · groundwater quality mapping using water quality data in the GIS environment is shown in Figure (3). The water

Merit Research Journal of Agricultural Science and Soil Sciences (ISSN: 2350-2274) Vol. 5(2) pp. 024-039, February, 2017 Available online http://meritresearchjournals.org/asss/index.htm Copyright © 2017 Merit Research Journals

Original Research Article

Mapping of Groundwater Quality in Northern Sinai Using GIS Technique

Ahmed Ibrahim Mohamed* and Mohamed A. A. Hassan

Abstract:

Soil and Water Department – Faculty of Agriculture – Suez Canal University

– Ismailia – Egypt - 41522

*Corresponding Author’s E-mail: [email protected]

Tel.: +201010035003

The present study aims to assess the quality of water wells scattered in the northern part of the province of Sinai, and estimate their suitability for use in irrigation of agricultural crops as a source or tributary of sustainable development in the Northern Sinai. To achieve this goal were collected 21 samples of groundwater from wells in different locations in the northern Sinai to conduct chemical analyzes and assess their suitability for irrigation. The water samples well were recorded for each well location using a GPS (Global Position System) for signing the maps to illustrate the distribution of the samples (wells) in the study area. Enhanced Thematic Mapper Plus (ETM+) images, a geographic information system (GIS) and field work collections of water samples were integrated to identify the groundwater potential areas in the Northern Sinai. This is in addition to four resulted Kriging models (Simple, Ordinary, Disjunctive and Probability) were tested for all 21 water well samples and mapping of the wells studied, as well as the signing of the most important results obtained from chemical analysis and evaluation of different values for those water wells in the study area. Statistical analyzes were performed chemicals characteristics of water quality, according to United States Salinity Laboratory (USSL) and the Food and Agriculture Organization (FAO) to assess the validity of water for irrigation for all water samples collected. The parameters determined were, temperature (T), total concentration of salinity (EC), concentration of cations and anions, hydrogen ion concentration average (pHc), sodium adsorption ratio (SAR), sodium adsorption ratio adjusted (Adj SAR), proportion of modified sodium (Adj RNa), percentage of sodium dissolved (SSP), residual sodium carbonate (RSC), effort salinity (PS), exchangeable sodium percentage (ESP), effective salinity (ES), Langelier Saturation Index (LSI), which expresses the extent of calcium carbonate saturation of the water, Ryznar Index (RI) expresses the ability of the water to make erosion, (pHs) and reflects the degree of acidity of the water when there is a saturation with calcium carbonate, and guide Saturation Index (SI). The results showed that the pH values were in the right range (7.4 to 8.8), and the salt concentration ranged from 0.4 to 16.2 dS/m. The concentration of the Cations in the appropriate term with the rule of sodium ion, followed by calcium, and anions were also at the appropriate term with the rule chloride followed by sulfate. The quality indicators they indicate that the salt concentration of the water wells located between the higher (42.37%), and very high (49.24%). The values of sodium adsorption ratio were in the appropriate range 88.55% less than 10%. And other quality indicators were between appropriate and higher in some cases. Key words: Groundwater, North Sinai, GIS, Water Quality

INTRODUCTION The Sinai Peninsula or Sinai nicknamed the land of turquoise, is a semi-desert island triangular west Asia, in the north-east of the Arab Republic of Egypt. Sinai area about 60,088 square kilometers, representing 6% of the

total area of Egypt. It is bordered to the north of the Mediterranean and west Gulf of Suez and the Suez Canal, and east Gaza Strip, occupied Palestine, and the Gulf of Aqaba, and south of the Red Sea, which is considered as

Mohamed and Hassan 025

Figure 1a. Geologic map of study area in northern Sinai.

a liaison between the continents of Africa and Asia. The population of Sinai Peninsula, about 1.400.000 people, according to general statistics 2013.

An important strategy is the increasing of water productivity to increase the production of food. Accordingly, increasing water productivity is an important strategy to increase food production (Abd-Alrahman and Samah 2011; Rosegrant et al., 2002) under conditions of restricted water supply. An important consideration is water use efficiency, where, irrigation water resources are diminishing and where rainfall is a limiting factor. Regardless, it’s critical that growers get the most out of every liter of available water, whether that water comes through underground water, rainfall, or both of them.

The main objective of the present study is to assess chemical groundwater and achieved mapping distributions of characteristics of water wells and its suitability for agricultural uses for soils in the Northern Sinai. Also, the current study is to evaluate and monitor the status of groundwater quality and assesses its suitability for irrigation; to determine spatial distribution of groundwater quality parameters and to generate groundwater quality map for the Northern Sinai. MATERIALS AND METHODS Study area is geographically located between 32° 32´ 38'' - 33° 21´ 09'' E and 30° 51´ 38'' - 31° 14´ 39'' N, in the northwestern of Egypt. The northern Sinai coast is existing at the rainy belt of Egypt; while the aridity increases expands for the most part toward the south (El-Ghazawi,

1989). Rainfall is scarce and varies from place to place and increases in the northeastern direction, ranging from about 30 mm/year in the southwest at Ismailia to about 300 mm/year in the northeast at Rafah. The annual rainfall in northwest Sinai varies between 36 to 54.8 mm/year and the total quantity of rainfall generally increases northward (El-Sheikh, 2008). The area is considered one of the horizontal expansions in the Sinai Peninsula which aims at establishing a link between Nile Delta and North Sinai by El Salam Canal. The ongoing project aims at reclamation of 400.000 feddans (Hafez, 2005 and Mohamed, 2013). Groundwater is the one available source of water in the study area beside support of El-Salam canal, so the assessment of agricultural potentiality in the Northern Sinai area requires water resources evaluation.

Several reviews such as (Said, 1990 and Deiab, 1998) had studied the geology and geomorphology of the area under study. The Northwestern Sinai is conserved by Quaternary deposits. The Pleistocene precipitates include: Sahl El-Tineh formation which composed of a mixture of black and white sands with silt, Al-Qantara formation which comprises of sand and grits with minor clay interbeds, coquina deposits, fanglomerates, and alluvial hamadah deposits (Figure 1a).

According to El-Asmar 1999; Deiab 1998 and Assal, 1999, Geomorphologically, Northwestern Sinai embodies five distinctive units are; 1) Coastal area, which includes old shore, coastal sand dunes, the strand plain of successive beach ridges with intervening runnels recording shoreline progradation during Late Holocene, and deltaic plain covered by mouth bar and distributaries channel fill sands; 2) El-Bardawil Lagoon; 3) The aeolian

026 Merit Res. J. Agric. Sci. Soil Sci.

Figure 1b. Geomorphology map of study area in northern Sinai.

Figure 2. Location image map of water well samples sites in northern Sinai.

sand which covers the majority of north Sinai and consists of wind-laid sediments including aeolian siliclastic sabkhas; 4) Mobile sand dunes; and 5) Salt marshes and sabkhas, Figure 1b.

To assess the quality of groundwater irrigation water in the province of the northern Sinai was selected number twenty one underground wells in some areas in the different geomorphologic units from the North Sinai Governorate. Twenty one of water samples were collected in plastic containers pint capacity from different locations.

The wisest to close the containers while conducting chemical analyzes them. And record the geographical location of each well using a device of the GPS (Global Position System) for signing on satellite imagery and map to illustrate the distribution of the samples (wells) in the study area (Figure. 2).

Water quality maps were created for various water properties and surfaces were articulated using Kriging interpolation technique. A salinity hazard map was prepared to show regions with low, medium and high


Figure 3. Flow chart of methodology adopted for groundwater quality mapping.

salinity hazards. Thus the final groundwater quality map for irrigation purpose was prepared by overlying the above mentioned grid data. Finally the study area was delineated into three classes on the basis of groundwater quality for irrigation purposes: suitable, moderate and unsuitable. The flow chart of the methodology adopted for groundwater quality mapping using water quality data in the GIS environment is shown in Figure (3).

The water quality data (attribute) were linked to the sampling location (spatial analysis) in ArcGIS and maps showing spatial distribution were prepared to easily identify the variation in concentrations of the groundwater parameters at various locations in the study area. Different water quality maps were produced using point data like pH, EC, TDS, Na+ and Mg++ by ArcGIS 10.2 software. Geostatistical analyses were performed using the

Geostatistical analysis (four Kriging models) extension available in ESRI ArcGIS 10.2 [ESRI, 2008]. Kriging differs from other methods, in which the weight function is no longer arbitrary, being calculated from the parameters of the fitted semivariogram model under the conditions of unbiasedness and minimized estimation variance for the interpolation. Thus, Kriging is regarded as a best linear unbiased estimation (BLUE).

To assess the quality of the water was carried out the following estimates: Measurement of pH using a device the pH meter, electrical conductivity (EC) device using the Conductivity meter, Calcium and Magnesium ions in water samples using the calibration solution in a (Na-EDTA). Sodium and Potassium ions in water sampling using spectrum resulting from Flame Photometer in the presence of an appropriate calibration curve. Carbonate

028 Merit Res. J. Agric. Sci. Soil Sci. and Bicarbonate in the samples measured using the calibration solution of sulfuric acid 01.0 N in the presence of phenolphthalein evidence in the case of the carbonate ion, and the evidence in the case of methyl orange bicarbonate ion. Chloride ion titration using a silver nitrate solution 0.5 N standard in the presence of potassium dichromate Guide (Richards, 1954). Sulfates ion through the work hanging from the barium sulfate added solution barium chloride to the sample and then measuring the turbidity by using the device for measuring turbidity, Williams and Steinberg, (1958) and the calculated concentration of reading on the device and the calibration curve fitting. Several indicators were used to assess the quality and validity of irrigation water, which depends on its effects on plants and soil, (Ayers and Westcot, 1994). These are: Electrical Conductivity (ECw) Units of electrical conductivity dS m-1. It also expresses the concentration of salts in the irrigation water, the amount of total dissolved salts (TDS) where expressed mgl-l. TDS (mg/l) = ECiw (dSm-1) x 640 (ECiw > 5 dS/m) TDS (mg/l) = ECiw (dSm-1) x 800 (ECiw < 5 dS/m) Sodium adsorption ratio (SAR) Calculated from the equation:

𝑆𝐴𝑅 = 𝑁𝑎

√𝐶𝑎 + 𝑀𝑔2

Where the calculated concentration unit (meq l-1) Sodium adsorption ratio adjusted (Adj. SAR)

𝑎𝑑𝑗𝑆𝐴𝑅 = 𝑁𝑎

√𝐶𝑎 + 𝑀𝑔2

⌊1 + (8.4 − 𝑝𝐻𝑐)⌋

𝑝𝐻𝑐 = (𝑝𝐾2 − 𝑝𝐾𝑐) + 𝑝(𝐶𝑎 + 𝑀𝑔) + 𝑝(𝐴𝑙𝑘) Calculated values of special tables and can be calculated from the following equations (Ayers and Westcot, 1994) (𝑝𝑘2 − 𝑝𝑘𝑐 = 2.107 ∗ (𝐶𝑎 + 𝑀𝑔 + 𝑁𝑎)0.038) 𝑝(𝐶𝑎 + 𝑀𝑔) = 3.298 − 0.34 ln(𝐶𝑎 + 𝑀𝑔) 𝑝𝐴𝑙𝑘 = 2.998 − 0.34 ∗ 𝑙𝑛(𝐶𝑂3 + 𝐻𝐶𝑂3)

Adj. Sodium Ratio (Adj. RNa) Since the resulting values of the SAR previous account gives high values has been suggested (Suarez, 1981) a new value is the ratio of sodium modified Adj. RNa, calculated from the following relationship:

𝐴𝑑𝑗 𝑅𝑁𝑎 = 𝑁𝑎

√𝐶𝑎𝑋 + 𝑀𝑔2

Where Cax is the value of calcium concentration rate (meq l-1), a calcium concentration in the irrigation water rate according to the salt concentration and the ratio of bicarbonate to calcium and pressure of carbon dioxide, which is extracted from special tabulations (Ayers and Westcot, 1994), or can be calculated from the following equation (according to the values shown in the table mentioned):

𝐶𝑎𝑋 = 2.09 ∗ 𝐸𝐶0.100398 ∗ (𝐻𝐶𝑂3

𝐶𝑎)

−0.66721

Soluble Sodium Percentage (SSP) It is a ratio of dissolved sodium cations to total soluble, and expressed the following relationship (Todd, 1980):

𝑆𝑆𝑃 = 𝑁𝑎+ ∗ 100

𝐶𝑎2+ + 𝑀𝑔2+ + 𝑁𝑎+ + 𝐾+

Residual Sodium Carbonate (RSC) They express the possibility of deposition of calcium or magnesium in irrigation water when increasing the concentration of dissolved carbonates, calculated from the following relationship (Richards, 1954, Eton, 1950): 𝑅𝑆𝐶 = (𝐶𝑂3 + 𝐻𝐶𝑂3) − (𝐶𝑎2+ + 𝑀𝑔2+)𝑚𝑒𝑞𝑙−1 Salinity potential (PS) Expresses the influence qualitative chloride ion and sulfate, and is calculated from the following relationship (Doneen, 1958):

𝑃𝑆 = 𝐶𝑙− + 0.5 ∗ 𝑆𝑂4 2− 𝑚𝑒𝑞𝑙−1

Exchangeable Sodium Percentage (ESP) They value ratio of sodium predicted if used water with a high concentration of sodium, calculated from the following relationship (Richards, 1954):

𝐸𝑆𝑃 = 100 ∗ (−0.0126 + 0.01475 ∗ 𝑆𝐴𝑅)

1 + (−0.0126 + 0.01475 ∗ 𝑆𝐴𝑅)

Langelier Saturation index (LSI) According to Burton et al., (2009) and Carrier Air Condit-

Mohamed and Hassan 029 Table 1. Some chemical analyses of selected well water in North Sinai.

Water Sample No.

Elev. By meter

T° pH EC dSm-1

TDS mg/l

Cations meq/l Anions meq/l

Ca2+ Mg2+ Na+ K+ CO32- HCO3 - Cl- SO4 2-

1 11 22.2 7.5 0.40 250 1.2 1.0 1.5 0.2 1.0 1.1 1.5 0.4

2 8 22.3 7.6 0.70 426 2.0 1.0 3.5 0.2 2.0 2.1 2.4 0.6

3 31 22.5 7.8 0.90 583 2.3 1.5 4.7 0.7 2.1 2.8 3.2 0.9

4 7 22.6 7.6 0.50 330 1.5 1.0 4.5 0.2 1.2 1.8 1.8 0.2

5 12 22.4 7.7 2.1 1363 4.5 3.5 13 0.4 4.0 5.6 9.1 2.4

6 8 22.5 7.8 4.6 2963 9.0 11 32 0.7 10 13 19 4.0

7 14 22.3 7.8 3.7 2342 5.0 7.0 27 1.0 7.0 8.0 17 5.0

8 17 22.5 8.3 1.1 7115 2.5 2.5 5.9 0.3 2.0 3.5 4.5 1.0

9 12 22.6 7.6 16.2 12960 43 28 109 1.0 28 46 89 7.0

10 4 22.5 7.9 9.1 7280 23 15 72 0.7 12 30 33 2.1

11 19 22.5 8.7 1.4 870 5.0 3.5 5.1 0.3 4.1 5.3 4.1 0.8

12 4 22.5 8.2 12.2 9760 24 21 104 1.4 19.2 28.4 71 3.4

13 13 22.6 7.6 5.2 4160 15 9.5 25 2.5 10.5 18.1 21.4 3.0

14 2 22.5 7.4 2.8 1792 7.6 5.0 17 0.6 6.2 9.5 11.3 1.0

15 4 22.5 7.8 2.2 1408 7.4 4.9 9.6 0.5 4.9 8.1 8.3 0.9

16 9 22.5 7.9 5.2 4184 15 12 26 0.3 1.7 6.7 37 8.1

17 14 22.8 8.8 8.0 6424 21 17 41 0.3 1.2 5.2 61 12

18 12 22.6 7.9 6.3 5040 13 7.7 40 1.2 1.1 12 44 6.4

19 14 22.8 8.0 9.0 7200 17 9.2 63 1.3 1.0 18 65 6.3

20 11 22.5 8.0 5.5 4400 15 9.8 30 0.9 0.9 12 33 9.4

21 9 22.5 8.0 4.4 2816 14 7.2 22 1.2 0.5 13 26 5.2

Table 2. Some chemical analyses of selected well water in North Sinai.

Well No. SAR (meq/l)0.5

pHc Adj SAR Adj. RNa

SSP %

RSC meq/l

ES meq/l

PS meq/l

ESP %

pHs LSI RI SI

1 1.4 8.2 1.7 1.1 38.5 -1.1 1.7 2.3 0.8 8.4 -0.93 9.3 -0.7

2 2.9 7.8 4.4 2.7 52.2 -0.8 3.7 3.8 2.8 8.0 -0.37 8.4 -0.2

3 3.4 7.7 5.9 3.5 51.1 -0.8 5.3 5.2 3.6 7.8 -0.02 7.8 0.1

4 4.0 8.1 5.2 3.4 62.5 -1.1 2.7 3.4 4.3 8.1 -0.33 8.6 -0.5

5 6.5 7.2 14.2 7.5 60.7 -2.4 13.3 13.2 7.3 7.3 0.35 6.9 0.5

6 10.1 6.6 28.1 12.4 60.7 -7.0 26.3 35.0 11.9 6.8 0.98 5.8 1.2


Table 2. Continue

ioning Company (1985), The Langelier Saturation \ index (LSI) is an equilibrium model derived from the theoretical concept of saturation and provides an indicator of the degree of saturation of water with respect to calcium carbonate. It can be shown that the Langelier saturation index (LSI) approximates the base 10 logarithm of the calcite saturation level. The Langelier saturation level approaches the concept of saturation using pH as a main variable. The LSI can be interpreted as the pH change required bringing water to equilibrium. Water with a Langelier saturation index of 1.0 is one pH unit above saturation. Reducing the pH by 1 unit will bring the water into equilibrium.

The LSI is possibly the utmost exceedingly used indicator of cooling water scale potential. It is simply an equilibrium index and deals only with the thermodynamic driving force for calcium carbonate scale formation and growth. It gives no sign of how much scale or calcium carbonate will actually precipitate to bring water to equilibrium. It simply

indicates the driving force for scale formation and growth in terms of pH as a master variable. In order to calculate the LSI, it is necessary to know the alkalinity (mg/l as CaCO3), the calcium hardness (mg/l Ca2+ as CaCO3), the total dissolved solids (mg/l TDS), the actual pH, and the temperature of the water (oC). If TDS is unknown, but conductivity is, one can estimate mg/l TDS using a conversion table such as the one presented here. LSI is defined as: LSI = pH - pHs Where, pH is the measured water pH and pHs is the pH at saturation in calcite or calcium carbonate. The Ryznar Index (RI) The Ryznar Index (RI) is an alternative method to the LSI for computing calcium carbonate scale formation. The RI is given by the following expression:

RI = 2pHsat - pH This is directly related to the LSI by:

RI = pH – 2LSI This value is computed using the pH of the water sample and the saturation pH, pHsat, as determined for the calculation of the LSI. RESULTS AND DISCUSSIONS The quality of groundwater is mainly affecting the chemical characteristics of aquifer, northwest Sinai. From the chemical analyses given in Tables (1 and 2), the following properties could be deduced: The pH values of groundwater mostly reflect alkaline conditions range from 7.4 to 8.8 were in the range appropriate with an average value of 7.88 for study area. The total dissolved solids (TDS) range from 250 to 12960 mg/l (average 4042.5 mg/l), while the salt concentration (EC) ranged 0.4 to 16.2 dS/m, with an average

7 11.0 6.9 27.7 12.8 67.5 -2.0 24.6 27.5 14.4 7.2 0.55 6.6 0.9

8 3.7 7.5 7.0 3.9 52.7 -1.5 6.1 6.8 3.4 8.2 0.14 8.1 0.8

9 18.3 6.0 62.0 26.9 60.2 -45.0 91.0 136.5 20.9 6.0 1.6 4.4 1.6

10 16.5 6.7 45.3 19.3 65.0 -29.5 53.0 87.5 22.9 6.3 1.6 4.7 1.2

11 1.5 7.2 3.3 1.7 24.8 -6.0 3.6 7.8 0.7 7.3 1.4 5.9 1.4

12 21.9 6.6 61.3 28.0 69.1 -36.0 77.0 117.5 27.5 6.4 2.3 4.6 1.6

13 9.6 6.6 26.9 10.5 57.7 -5.5 32.5 44.2 11.9 6.5 1.1 5.4 1.0

14 6.8 6.9 16.7 8.6 56.3 -4.6 15.4 20.3 8.4 6.9 0.46 6.4 0.5

15 3.7 6.8 9.7 4.4 40.9 -3.4 8.6 19.8 3.9 7.0 0.82 6.2 1.0

16 7.1 6.8 18.3 8.8 48.8 -20.3 25.3 41.1 8.1 7.0 0.93 6.1 1.1

17 9.4 6.7 25.4 11.9 51.7 -30.8 42.3 67.0 10.8 7.0 1.8 5.2 2.1

18 12.4 6.7 34.1 17.0 64.6 -8.7 42.3 47.2 13.7 6.8 1.1 5.7 1.2

19 17.4 6.4 51.5 25.3 69.6 -8.2 63.8 68.2 21.9 6.6 1.4 5.2 1.5

20 8.5 6.6 23.9 11.6 53.9 -12.8 30.2 37.7 10.4 6.7 1.3 5.4 1.5

21 6.8 6.6 19.0 9.6 49.5 -8.2 22.8 28.6 8.8 6.6 1.4 5.2 1.4

http://www.corrosion-doctors.org/Cooling-Water-Towers/ph.htm

http://www.corrosion-doctors.org/Water-Glossary/Glossary.htm

http://www.corrosion-doctors.org/Cooling-Water-Towers/Index-Lang-TDS.htm

http://www.corrosion-doctors.org/Cooling-Water-Towers/Index-Lang-TDS.htm


Figure 4. The spatial distribution maps of pH (A), TDS (B), EC (C), Na+ (D), Mg++ (E) and Elevation (F) for water well samples from study area in northern Sinai

value of 4.86 dS/m in study area (Table 1). The salinity decreases at some patches located along El-Qantara Shark/El-Arish Road. The Quaternary groundwater along this road is affected by seepage from municipal water

showed the spatial distribution maps of pH, TDS and EC in Figure 4 (A, B and C), respectively. Sodium represents the dominant cation in the majority of the analyzed groundwater samples; varies between 1.5 and 109 meq/l


Table 3. Geostatistical analysis of Kriging Modelling estimated for groundwater parameters in well water samples collected from study area in the northern Sinai.

Water Quality Parameters

Kriging Modelling

Mean Root Mean

Square

Mean Standardized

Root Mean Square

Standardized

Average Standard

Error

Regression Function

LSI Simple -0.04 0.46 -0.06 0.98 0.49 0.55

SAR Disjunctive -0.18 5.58 -0.03 0.95 5.17 0.17

RSC Ordinary -0.13 12.38 -0.05 0.97 9.73 0.27

ES Ordinary -0.41 23.14 -0.01 1.03 20.91 0.33

PS Probability -0.02 0.49 -0.03 1.04 0.46 0.23

ESP Simple 0.09 7.41 0.03 1.01 6.78 0.15

EC Probability -0.03 0.49 -0.03 1.02 0.46 0.21

SI Simple -0.04 0.49 -0.07 0.98 0.49 0.53

SSP Ordinary -0.19 11.79 -0.02 1.02 11.55 0.12

TDS Ordinary -41.46 311.33 -0.01 1.01 577.71 0.38

RI Probability -0.01 0.51 -0.02 0.97 0.53 0.37

pH Simple 0.01 0.31 0.01 0.99 0.29 0.35

cpH Disjunctive 0.05 0.52 0.07 1.02 0.52 0.15

spH Disjunctive 0.04 0.49 0.07 1.00 0.51 0.14

Adjsar Simple -0.98 18.12 -0.05 1.04 16.12 0.21 -Cl Ordinary -0.14 23.16 -0.01 1.01 21.31 0.35 +Na Disjunctive -2.36 28.32 -0.08 0.98 28.64 0.17

+K Ordinary -0.04 0.62 -0.05 1.00 0.62 0.11 --

3 CO Ordinary -0.13 6.46 -0.02 1.06 5.46 0.28 -

3 HCO Ordinary -1.22 10.08 -0.09 1.04 8.97 0.11 --

4 SO Disjunctive -0.18 3.22 -0.05 0.99 3.25 0.15

with an average of 31.69 meq/l. The highest Na+

concentrations are recorded near the Mediterranean Sea. Sodium, chloride and sulphate ions display a nearly linear increase with increasing salinity of Quaternary groundwater show the sodium distribution image map in Figure 4 (D). Magnesium ranges from 1 and 28 meq/l with an average of 8.56 meq/l. The high values of magnesium reflect the abundance of magnesium salts that formed by sea water intrusion at near well No. 9, show in Figure 4 (E). Potassium represents the least dominant cation; ranges from about 0.2 to 2.5 meq/l with an average of 0.74 meq/l for the study area in northern Sinai. Calcium ranges between 1.2 and 43 meq/l with an average of 11.7 meq/l. Calcium concentrations increase generally towards northeast direction due to leaching and solubility processes of calcium carbonate rich deposits (Kurkar) due east. Similar conclusions have been suggested by El-Osta (2000) and Mohamed (2007). Chloride ranges from 1.5 to 89 meq/l. The highest concentrations are recorded near the Mediterranean Sea at well No. 9 due to sea water encroachment. Sulphate content ranges from 0.4 to 9.4 meq/l. Bicarbonate content ranges between 1.1 and 28.4 meq/l, while the Carbonate content ranges between 1 and 19.2 meq/l with an averages of 11.86 and 6.01 meq/l, respectively. The concentration of cations were some of the wells in the range appropriate to the rule of the sodium ion, followed by calcium, and anions were also some of the wells in the range appropriate to the rule of chloride

followed by bicarbonate. The elevation map was supported the distribution and concentration of cations (Na+ and Mg++), pH, TDS and EC parameters of water well samples showed in Figure 4 (F). These maps were achieved by different kriging models (Table 3) from ArcGis 10.2 V software.

Thirteen characteristic water quality measurements has calculated by different equations on all water samples collected from the study area to determine the status and well water quality in the northern Sinai study area, these properties will be discussed and spatial distribution maps in the following paragraphs.

Sodium adsorption ratio (SAR) values arrange between, lowest value 1.4 and highest value 21.9, while the values of Adj SAR were of higher values where the less the value of 1.7 and a larger value of 62.0. While a high salt content (high EC) in water leads to formation of saline soil, high sodium content (SAR) leads to development of an alkaline soil. Irrigation with Na-enriched water results in ion exchange reactions: uptake of Na+ and release of Ca++ and Mg++ (Khodapanah et al., 2009). This causes soil aggregates to disperse, reducing its permeability (Tijani, 1994). The ratio of sodium modified Adj RNa had values less where the largest value of 27.9 and the lowest value of 1.1.

Residual sodium carbonate (RSC) has been calculated to determine the hazardous effect of carbonate and bicarbonate on the quality of water for agricultural


Figure 5. The spatial distribution maps of SAR (A), Adj.SAR (B), Adj. RNa (C), RSC (D) for water well samples from study area in northern Sinai

purposes. RSC was negative in most values, and this means, total concentration of calcium and magnesium greater than sum of carbonate and bicarbonate concentration. In water having high concentration of bicarbonates, there is tendency for calcium and magnesium to precipitate as the water in the soil becomes more concentrated. As a result, the relative proportion of sodium in the water is increased in the form of sodium bicarbonate (Sadashivaiah et al., 2008). The analyzed water well samples in study area in northern Sinai were in the suitable class of water qualty.

The spatial distribution maps of characteristic of water well samples for SAR, Adj SAR, Adj RNa and RSC values were showed in Figures 5 (A, B, C and D), respectively. These spatial distributions were prepared using Disjunctive, Simple and Ordinary kriging exponential models (Table 3) from ArcGis V. 10.2.

The percentage of sodium dissolved SSP results showed also that about 40% of the wells was less than

60% and this classifies safe water for irrigation and about 60% of the wells less than 75% water medium validity irrigation depending on the division of plant salinity US. The results of the hydrogen ion concentration average (pHc) in all wells studied values less than 8.4 and this means that the water is slanted to precipitate calcium. The results of salinity effective (PS) which represents the total salinity minus total calcium and magnesium, the lowest value was 2.3 and the largest value of 136.5 meq/l. The results also showed that the percentage of sodium is also expected to cross the land irrigated by the quality of this water (ESP) ranged from 0.8 % up to the largest value of 27.5 %.

The spatial distribution maps of SSP, pHc, PS and ESP in the study area of northern Sinai are showed in Figure 6 (A, B, C and D), respectively. These maps were prepared using of Ordinary, Disjunctive, Probability and Simple kriging models, respectively from ArcGis V. 10.2


Figure 6. The spatial distribution maps of SSP (A), pHc (B), PS (C) and ESP (D) for water well samples from study area in northern Sinai

Langelier Saturation Index (LSI) The saturation levels indicators of sparingly soluble salts in the concentrate stream are the Langelier Saturation Index (LSI) and the saturation ratios. The LSI provides an indication of the calcium carbonate saturation. Negative values of LSI indicate that the water is aggressive and that it will have a tendency to dissolve calcium carbonate. Positive values of LSI indicate the possibility of calcium carbonate precipitation (Table 4) and show the interpretation of LSI values in tables (5 and 6) according to Burton et al., 2009 and Carrier Air Conditioning Company 1985. The spatial distribution map of LSI and pHs were achieved by using of Simple and Disjunctive Kriging models from ArcGis program V. 10.2, showed that in Figures (7 and 8).

Groundwater quality assessment of some wells in the northern Sinai on Langelier Index (LSI) and Ryznar (RI)

was performed. Average Langelier index is 0.994, which has scaling conditions. Langelier index indicates that in most area of plain LSI > 0 that is indicator of tendency of water to carbonate precipitation. For controlling and eliminating the tendency of scale formation must utilize methods that are leading to pH reduction. In other words, pH changes from alkaline to acidic. Among the proposed solutions can be pointed to inject CO2 into the water, adding sediment maker materials such as Ortho-phosphates and Meta-phosphates, adding mineral acids into the water.

Langelier index was created using the spatial distribution of Gaussian Kriging model which tend to show increased scaling of groundwater from the north to the south of study area in the northern Sinai region. Given the positive Langelier index, water tends to be characterized by carbonate precipitation at these points. Using GIS models, the spatial distribution of Langelier index was


Table 4. The indications for the LSI and the improved LSI by Carrier are based on the following values

Water sample No.

pHs LSI Indication based on Langelier (1936)

Indication based on improved Langelier by

Carrier (1985)

1 8.4 -0.93

Water is undersaturated with respect to calcium carbonate. Undersaturated water has a tendency to remove existing calcium carbonate protective coatings in pipelines and equipment.

Serious corrosion

2 8.0 -0.37


Slightly corrosive but non-scale forming.

3 7.8 -0.02



4 8.1 -0.33



5 7.3 0.35 Water is supersaturated with respect to calcium carbonate (CaCO3) and scale forming may occur.

Slightly scale forming and corrosive.


Scale forming but non corrosive.












Serious corrosion




















Table 5. Interpretation of LSI values (Burton et al., 2009)

LSI Indication

LSI < 0 Water is under saturated with respect to calcium carbonate. Under saturated water has a tendency to remove existing calcium carbonate protective coatings in pipelines and equipment.

LSI = 0 Water is considered to be neutral. Neither scale-forming nor scale removing.

LSI > 0 Water is supersaturated with respect to calcium carbonate (CaCO3) and scale forming may occur.

Table 6. LSI vales (Carrier Air Conditioning Company 1985)

LSI (Carrier) Indication

-2,0 < -0,5 Serious corrosion

-0,5 < 0 Slightly corrosion but non-scale forming

LSI = 0,0 Balanced but pitting corrosion possible

0,0 < 0,5 Slightly scale forming and corrosive

0,5 < 2 Scale forming but non corrosive

Figure 7. The spatial distribution maps of LSI for water well samples in study area


Figure 8. The spatial distribution maps of pHs for water well samples in study area

Table 7. Ryznar Index classification

developed. According to Figure 7, the tendency to scale forming of groundwater from the north to the south of Sinai shows an increasing trend. Langelier index varies from -0.93 to 2.3 and in terms of this indicator, groundwater of most study area of the northern Sinai is scaling. Ryznar Index (RI) Using the following equation can be used to calculate the index value: RI = 2pHc –pH

Using Table 7, the water situation is characterized in terms of corrosion and scaling. Average of Ryznar index was 5.97 which indicate a neutral condition. Most well studied was in the range of 6.2 to 6.9 which indicates the water is neutral. Only at the two well, Ryznar index is 5.4 indicator of high scaling and 9 wells are placed in the category of slight scale forming. The spatial distribution map for Ryznar index was prepared using a Probability kriging exponential model in ArcGis V. 10.2. Zoning maps Ryznar index can be concluded that the status of

groundwater resources in the northern part of the Sinai is slightly corrosive. Middle part on the plain, with the largest area being in the range 6.9 to 6.2 is neutral status. Groundwater in the southern part of the Sinai, according to exposure in the range of 5.5 to 6.2, is slight scaling, showed that in Figure (9).

Ryznar index results showed that for most of the study area between Ryznar index values are 4.4 to 9.3 that according to Table 2, the water has a neutral situation. Ryznar index is 5.4 only for two wells and water is high scaling. Water situation to twelve points with respect to the Ryznar classification is 5.8 - 4.4 that is slightly scaling. According to Figure 9, the spatial distribution of Ryznar index shows that water is slightly corrosive.

Finally, according to the Langelier index and Ryznar can be concluded that although the status of groundwater in plain at low scale and corrosion is low, but the most of plain area is scaling. Using data obtained from the analysis of groundwater quality of Plain, Langelier index was calculated. Results showed that Langelier index is negative only for 4 Wells, given the negative Langelier index points and the classification criteria, corrosive water

Ryznar Index RI Water situation

< 5.5 Heavy scale

5.5 – 6.2 Scale

6.2 – 6.8 Neutral

6.8 – 8.5 Corrosive

> 8.5 Very corrosive


Figure 9. The spatial distribution maps of RI for water well samples in study area

conditions for these two wells are reported. The rest of the amount is greater than zero and is positive Langelier Index (LSI > 0). Validation Geostatistical analysis were achieved for groundwater quality parameters in all well water samples collected from study area in the northern Sinai. Kriging Modelling of geostatistics analysis were used for different water quality parameters in water wells from study area. In order to evaluate the model performance a cross-validation method in ArcGIS 10.2 V software was applied. ArcGIS software consists of similar environmental characteristics, compared to the study area in this research. Twenty one water well samples were collected and employed for models validation. Four resulted Kriging models (Simple, Ordinary, Disjunctive and Probability) were tested for all 21 water well samples in this research. Mean (M), Root Mean Square (RMS), Mean Standardized (MS), Root Mean Square Standardized (RMSS), Average Standard Error (ASE) and Regression Function (RF) are compared in Table 4. Finally, cross-validation test was used to assess the prediction performance of kriging with external drift compared with Simple, Ordinary, Disjunctive and Probability kriging models.

Geostatistical procedures were separately applied to each group of data by using a multivariate approach and fitting a linear model of coregionalization (LMC) to the experimental variograms. LSI, ESP, SI, pH and Adjsar data properties were interpolated with Simple kriging

model in studied water well samples. SAR, pHc, pHs, Na+ and SO4

-- data were interpolated with Disjunctive kriging model through a regular water well samples for spatial distribution maps and using ordinary kriging model for RSC, ES, SSP, TDS, Cl-, K+, CO3

-- and HCO3- data spatial

distribution maps. PS, EC and RI data were estimated using Probability kriging model for achieved for spatial distribution maps. The geostatistical analyses were performed with ArcGIS 10.2 V software. CONCLUSION The present research is conducted to give an insight on the geochemical aspects, evaluation and mapping of the Quaternary aquifer in northern Sinai, Egypt. The Quaternary aquifer is the most important source of water in the northern Sinai for agricultural purposes. For this study, 21 groundwater samples were collected from wells and analyzed for pH, Electrical Conductivity (EC), temperature, major ions, and TDS. Irrigational suitability of groundwater in the study region was evaluated using quality parameters, e.g., EC, SAR, RSC, RI and LSI method classification. Spatial analysis of various quality parameters of water wells in GIS environment was found to be effective and efficient. It exists under unconfined conditions. Thematic maps generated in the study will be helpful to planners and policy makers especially of public health and irrigation departments, for sustainable water management in a holistic way for the study area in the northern Sinai. The groundwater wells are mainly brackish to saline in character for total dissolved solids (TDS)

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Mapping of Groundwater Quality in Northern Sinai Using GIS ...€¦ · groundwater quality mapping using water quality data in the GIS environment is shown in Figure (3). The water